The present disclosure relates to service level agreements, and more particularly to generating models for, and predicting, an impact of a Service Level Agreement (SLA).
Complex service systems involving multiple parties in support of hardware and software requirements of customers are typically governed by an SLA. For example, a company may engage another party to provide a particular information technology (IT) service (e.g., account activation) governed by an SLA. The SLA may contain provisions related to the performance of the system and the costs associated with the service.
In this and other contexts, standardization is desirable from the service provider's perspective. While standard SLAs are designed to reduce service delivery costs, the ability to provide flexible and customized service levels can be important in gaining the customer's business. Quantifying and estimating the impact of non-standard SLAs on the service delivery cost remain a challenging task and rely on a handful of highly skilled service delivery experts.
To provide a systematic approach for SLA driven service delivery cost estimation, the relationships among service level constraints, customer service workload, and service personnel efficiency need to be characterized. Although literature exists using either analytical or simulation based approaches to support SLA based service delivery decision making, it typically requires detailed modeling data that is typically not available during service engagement.